Tomographic studies based on passive seismic measurements have proven to be a powerful tool to image the subsurface. This especially holds in areas like Iceland, where the microseism coverage arriving from the ocean is excellent. In this study, we apply Ambient Noise Seismic Interferometry (ANSI) to generate a tomographic image of Rayleigh-waves velocity anomalies to further invert for S-wave anomalies at two Icelandic locations. We derive a tomographic image over Reykjanes Peninsula geothermal system using 30 Broad-Band (BB) stations deployed under the IMAGE (Integrated Methods for Advanced Geothermal Exploration) project framework and operated for approximately one year and a half. In the other case study, we derive a tomographic image of Torfajökull volcano using 23 BB seismometers that recorded ambient noise for 100 days. The later data were acquired in 2005 by Cambridge University. We retrieve the surface-wave part of the Green’s functions by cross-correlation between station pairs and consecutive stacking of the cross-correlations to obtain coherent ballistic surface waves (BSW). We pick the arrival times of the BSW, which are the input for the tomographic analysis. Both datasets show remarkably high signal-to-noise ratio of surface-wave arrivals between 0.1 and 0.5 Hz, even with only 100 days of recorded ambient noise. A beamforming analysis indicates a broad azimuthal coverage with persistent ambient noise arrivals within three azimuthal quadrants - between 90 and 360 degrees. The highly coherent surface-wave retrieval and the wide azimuthal coverage of the microseisms explain the success of ANSI techniques in Iceland. For the tomographic inversion, we use a Tikhonov and a statistical regularisation to invert the ballistic surface-wave time-arrival to 3D frequency-dependent velocity variations. After further inversion to S-wave velocity variations, we detect low- and high-velocity anomalies with changes between -15% and 15% from an estimated average velocity, we interpret these anomalies as possible old dyke intrusions and heat sources.@en

The 2011 Tohoku-Oki earthquake with 9.0 Mw led to an enormous mass redistribution originated from large deformation due to faulting and had a massive impact on the coastal area of eastern Japan. While the satellite gravity mission GRACE (Gravity Recovery and Climate Experiment) can detect the gravitational change caused by this tremendous event, slip distributions are usually derived from GPS, seismic and (in the more particular case) tsunami data. We evaluate the differences between measured and modeled coseismic gravity changes for three fault slip models derived from either GPS and tsunami data, GRACE data, or a combination of all three data types. The data are weighted according to their measurement accuracy in a Bayesian joint inversion approach. We perform a long term average of GRACE data, which increases sensitivity and reduces artefacts, and find that the postseismic gravity change leaks into the derived mean gravity field. We try to reduce this problem by averaging only 6 months of postseismic GRACE data, where the postseismic gravity signal, which superimposes onto the coseismic signal of ≈ 6μGal (for a geometric based model) peaks approximately 3 months after earthquake occurrence. Consequently fault slip models merely derived from GPS (10 days avg.) and tsunami data (<5h time span) show deviations of ≈ 2 μGal to a GRACE 6 monthly averaged combined solution which indicates the difference accumulated from the geometric and gravimetric modeling and the postseismic gravity signal in the GRACE data.

@en

Geologist Andy Hooper explains why the chances of a huge eruption of the Bárðarbunga volcano in Iceland and massive disruption of air travel are low@en

The landslide activity in the area of Bolshoy Sochi (Big Sochi) situated at the Black Sea coast of the Great Caucasus has been studied using the StaMPS PS-InSAR method. We incorporated three sets of radar images from the satellites with different wavelengths ALOS, Envisat and Terra-SAR-X from both ascending and descending tracks which cover the time period from January 2007 to September 2012. Comparative investigation of surface displacements obtained from all the data sets is presented. Areas where high surface displacement rates have been located on the base of the satellite data coincide well with zones of high landslide activity according to ground observations. We constructed time series for the two landslides: in the Baranovka and Mamaika villages where considerable surface movements had been observed during the time of acquisitions. Analysis of the time series made it possible to determine periods of activity and relative stability of the landslides and compare them with ground observations.@en

Magmatic plumbing systems beneath active and moderately active volcanoes are often poorly constrained. A better knowledge of the shape, size and location of the magma bodies would enable us to better predict magma movements preceding an eruption. Surface displacements estimated from radar interferometry (InSAR) can be used in geophysical modelling to constrain location, geometry and pressure changes in magma systems. However, the resolution of the inferred magma chamber is typically poor. More insight into the location and geometry of magmatic systems can be gained using active-source reflection seismic surveys, which allow detection of velocity contrasts at the edges of the magma bodies. The drawback of this technique is that controlled-source surveys are expensive. As an alternative, seismic interferometry (SI) uses cross-correlation of natural signals to generate new seismic records that simulate active sources. Under the premise that both seismic and radar observations would help to narrow down the location, shape and size of a magma system, we present the first results of combined radar and seismic interferometric processing over Torfajökull volcano. Torfajökull is located in the neovolcanic zone, in the south of Iceland. The volcano is characterized by intense thermal manifestations (hot springs forming ground steaming and fumaroles) with higher activity nearby the faults of the active NE-SW fissure swarm. Torfajökull erupts infrequently, with only two eruptions in the last 1200 years, the latest of which was over 5 centuries ago. However, ongoing seismicity, deformation and geothermal activity indicate the continued presence of a long-lasting magma chamber. Although historical eruptions have been relatively small, the large caldera (18x12 km diameter) and high geothermal activity within the caldera is evidence of a massive eruption in the past, and the potential for a further eruption of similar size is unknown. We applied InSAR time series analysis to data acquired by Envisat over the Torfajökull region along 6 different tracks (3 tracks in ascending and 3 tracks in descending mode). The estimated velocity maps show subsidence beneath the SW part of the caldera. This subsidence has been on-going since at least 1993, with rates of up to ~13 mm/yr. This has been interpreted as a cooling magma chamber, shrinking at linear rates. To obtain a rough approximation of the geometry and location of the source of subsidence we ran a forward model. The model suggest an ellipsoidal magma chamber within the volcano caldera with a NE-SW orientation and at ~5km depth. For the SI processing we use two types of natural signals: microseisms and local earthquakes. We use seismic data acquired in 2005 at 30 stations sparsely distributed around the Torfajökull area. Using microseisms, we divide the noise, recorded at two stations in portions of 1h, cross-correlate the corresponding portions and then sum the correlated results. The result is a retrieved surface-wave part of the Green’s function between the two stations. This is repeated between all stations. Careful assessment of the quality of the retrieved Green’s functions for small time windows allows analysis of the microseism noise. The results show that the microseisms are dominant in the NW-SE direction and the resulting retrieved surface waves propagate at ~3 km/s in the double-frequency microseism band. The retrieved surface waves between the stations will be used in tomographic inversion that will allow derivation of the 3D S-wave velocity distribution in the subsurface. We will then use these results to better constrain our magma source model, currently constrained only by InSAR. @en

After a period of quiescence since a sill intrusion in 1999-2000, a subtle deformation signal was again detected at Eyjafjallajökull, beginning in the summer of 2009, at a continuous GPS station on the southern flank. At our request the German Space Centre (DLR) immediately began tasking the TerraSAR-X satellite to acquire three SAR images every 11 days, giving a time series of SAR images prior to the eruption with unprecedented temporal sampling (although interrupted by snow during the winter).
Previously we modelled individual interferograms that showed that there was a large uplift signal. We modelled this as a series of sills and a dike with a total volume of ~0.05 km3. During the flank eruption, beginning on 20 March, no significant deformation is detected, but coinciding with the start of the explosive eruption on April 14, we detected subsidence centred on the caldera. What we modelled showed us that Eyjafjallajökull was an unusual which we modelled …. This deformation does not relate to pressure changes within a single magma chamber.
Here we extend our analysis InSAR time series covering full eruptive period. After correcting for DEM errors and reduction of atmospheric signal, we have found a number of signals that we interpreted in terms of magma movement. These magma movements are separately analysed in 3 phases: pre-eruptive (inflation), co-eruptive (no deformation) and post-eruptive (deflation).
The displacement time series from June 2009 to 4 February 2010 (pre-eruptive-phase) shows line-of-sight shortening on the southwest flank of about 2 cm. The displacement signal is present in a set of interferograms and it has a consistent behaviour in time, implying that it is not due to atmospheric contamination. We performed atmospheric stratification over the entire Interferogram (4 Feb 2010) to check how much of the signal correlated with the topography would disappear when removed. The correlation coefficient over the southwest flank is very small compared with the signal from the entire interferogram. We can say that in this area not much of the atmospheric effects related with the topography are present, suggesting that the signal could be deformation.
For the co/post-eruptive phases we calculated phase difference between nearby points to check their evolution in time. In the southeast flanks we observe deflation through all analyzed period, while in western flanks of the volcano we observe Inflation during effusive eruption, followed by deflation during explosive eruption, and a new inflation pattern between 05 June and 19 July that we cannot explain. In preliminary modelling we fit this post-eruptive phase with a pressure decrease of an ellipsoidal source, equivalent to a volume reduction of ~0.03 km3.
The limitations when analysing this dataset are mainly concerning the phase unwrapping performance through ice- and ash-covered areas. This is caused by decorrelation owing to ash cover where there is almost complete loss of coherence. We applied new methods to overcome these limitations. To improve point density over the scene, we combined PS (Persistent Scatterers) and SB (Small Baselines) methods. By combining highly coherent interferograms, the increase of distributed scatterers is clear and the phase unwrapping performance improved. To detect and correct non-systematic unwrapping errors, we calculated azimuth and range offsets. Additionally, because of the fact that L band has higher penetration, we processed ALOS images trough single interferogram analysis. By these means we were able to extract more of the deformation signal around decorrelated areas.
@en